engleski

Assessing the health status of beech-fir forests using remote sensing methods

Forest health evaluation may be performed with terrestrial monitoring or with the application of remote sensing methods. Of remote sensing methods, interpretation of colour infrared (CIR) aerial photographs is particularly suitable. The primary goal of this research is to assess and evaluate the health status of beech-fir forests, obtain data on surface damage distribution and investigate some features that affect forest health in the area of Velebit with CIR aerial photographs interpretation. Forest damage inventory was made for the entire surveyed area using the raster method (100x100m) overlaid on the infrared digital orthophoto. Damage indicators for particular tree species and overall for the entire surveyed area were calculated. Regression analysis was used to determine inter-dependencies of geomorphological parameters and damage indicators. Photointerpretation of individual trees in a systematic sample in the study area covered a total of 21, 011 trees. As for fir, 61.96% of the trees are severely damaged. Within this percentage, the mean damage for fir is 51.03%. In the entire surveyed area, severely damaged beech accounts for 6.56%, which confirms that beech is the least damaged tree species. Geomorphological factors also affect a stand's health status. According to the obtained results, an increase in the slope is directly proportionate to the increase in the fir damage index. CIR aerial photographs were photointerpreted in order to determine and analyse the health condition of beech-fir forests in the area of Velebit and obtain data on surface damage distribution. According to the results, the damage degree of inventoried forests is at the transition from slight to moderate. It can be concluded from the results that damage increases with rising terrain slope and growing distance of terrain orientation from the west direction.

color-infrared (CIR) aerial photographs; beech-fir forests; health status; multivariate analysis; geomorphological factors

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